Stefano Iannucci

MOSES: A Framework for QoS Driven Runtime Adaptation of Service-Oriented Systems

Architecting software systems according to the service-oriented paradigm and designing runtime self-adaptable systems are two relevant research areas in todays software engineering. In this paper, we address issues that lie at the intersection of these two important fields. First, we present a characterization of the problem space of self-adaptation for service-oriented systems, thus providing a frame of reference where our and other approaches can be classified. Then, we present MOSES, a methodology and a software tool implementing it to support QoS-driven adaptation of a service-oriented system. It works in a specific region of the identified problem space, corresponding to the scenario where a service-oriented system architected as a composite service needs to sustain a traffic of requests generated by several users. MOSES integrates within a unified framework different adaptation mechanisms. In this way it achieves greater flexibility in facing various operating environments and the possibly conflicting QoS requirements of several concurrent users. Experimental results obtained with a prototype implementation of MOSES show the effectiveness of the proposed approach.

Designing a Broker for QoS-driven Runtime Adaptation of SOA Applications

One of the major current trends in service-oriented systems is the emphasis given to the need of introducing runtime adaptation features, so that the system can meet its QoS requirements in a volatile operating environment. In this paper we present the design and implementation of a service broker that supports the QoS-driven runtime adaptation of SOA applications offered as composite services to users. We describe the functionalities provided by the broker components and present their design and implementation according to two different versions we have developed and that are both based on open source products. The components of the first version have been developed in Java as Web services, while the second version takes advantage of OpenESB. Since the broker needs to sustain a traffic of requests generated by several concurrent users, we also present the replicated architectures of the two broker versions. We discuss the design tradeoffs and the lesson we have learned in developing the broker.

A Scalable and Highly Available Brokering Service for SLA-Based Composite Services

The introduction of self-adaptation and self-management techniques in a service-oriented system can allow to meet in a changing environment the levels of service formally defined with the system users in a Service Level Agreement (SLA). However, a self-adaptive SOA system has to be carefully designed in order not to compromise the system scalability and availability. In this paper we present the design and performance evaluation of a brokering service that supports at runtime the self-adaptation of composite services offered to several concurrent users with different service levels. To evaluate the performance of the brokering service, we have carried out an extensive set of experiments on different implementations of the system architecture using workload generators that are based on open and closed system models. The experimental results demonstrate the effectiveness of the brokering service design in achieving scalability and high availability.

A performance comparison of QoS-driven service selection approaches

Service selection has been widely investigated as an effective adaptation mechanism that allows a service broker, offering a composite service, to bind each task of the abstract composition to a corresponding implementation, selecting it from a set of candidates. The selection aims typically to fulfill the Quality of Service (QoS) requirements of the composite service, considering several QoS parameters in the decision. We compare the performance of two representative examples of the perrequest and per-flow approaches that address the service selection issue at a different granularity level. We present experimental results obtained with a prototype implementation of a service broker. Our results show the ability of the per-flow approach in sustaining an increasing traffic of requests, while the per-request approach appears more suitable to offer a finer customizable service selection in a lightly loaded system.

A new approach to QoS driven service selection in service oriented architectures

Service selection has been widely investigated by the SOA research community as an effective adaptation mechanism that allows a service broker, offering a composite service, to bind at runtime each task of the composite service to a corresponding concrete implementation, selecting it from a set of candidates which differ from one another in terms of QoS parameters. In this paper we present a load-aware per-request approach to service selection which aims to combine the relative benefits of the well known per-request and per-flow approaches. We present experimental results obtained with a prototype implementation of a service broker. Our results show that the proposed approach is superior to the traditional per-request one and combines the ability of sustaining large volume of service requests, as the per-flow approach, while at the same time offering a finer customizable service selection, as the per-request approach.

Designing a flexible and modular architecture for a private cloud: a case study

Cloud computing is an emerging paradigm used by an increasingly number of enterprises to support their business and promises to make the utility computing model fully realized by exploiting virtualization technologies. Free software is now mature not only to offer well-known server-side applications, but also to land on desktop computers. However, administering in a decentralized way a large amount of desktop computers represents a demanding issue: system updates, backups, access policies, etc. are hard tasks to be managed separately on each computer. This paper presents a general purpose architecture for building a reliable, scalable, flexible, and modular private cloud that exploits virtualization technologies at different levels. The architecture can be used to offer a variety of services that span from web applications and web services to soft real-time applications. To show the features of the proposed architecture, we also present the design and implementation over it of a Linux Terminal Server Project (LTSP) cluster that benefits from the underlying IaaS services offered by the private cloud. The cloud infrastructure, as well as the LTSP, have been implemented exclusively using free software and are now in a production state, being used by approximately 200 users for their everyday work. We hope that our description and design decisions can provide some guidance about designing an architecture for a cloud service provider.

Cloud Desktop Workload: A Characterization Study

Today the cloud-desktop service, or Desktop-as-a-Service (DaaS), is massively replacing Virtual Desktop Infrastructures (VDI), as confirmed by the importance of players entering the DaaS market. In this paper we study the workload of a DaaS provider, analyzing three months of real traffic and resource usage. What emerges from the study, the first on the subject at the best of our knowledge, is that the workload on CPU and disk usage are long-tail distributed (lognormal, weibull and pare to) and that the length of working sessions is exponentially distributed. These results are extremely important for: the selection of the appropriate performance model to be used in capacity planning or run-time resource provisioning, the setup of workload generators, and the definition of heuristic policies for resource provisioning. The paper provides an accurate distribution fitting for all the workload features considered and discusses the implications of results on performance analysis.

MOSES: A Platform for Experimenting with QoS-Driven Self-Adaptation Policies for Service Oriented Systems

Architecting software systems according to the service-oriented paradigm, and designing runtime self-adaptable systems are two relevant research areas in today’s software engineering. In this chapter we present MOSES, a software platform supporting QoS-driven adaptation of service-oriented systems. It has been conceived for service-oriented systems architected as composite services that receive requests generated by different classes of users. MOSES integrates within a unified framework different adaptation mechanisms. In this way it achieves a greater flexibility in facing various operating environments and the possibly conflicting QoS requirements of several concurrent users. Besides providing its own self-adaptation functionalities, MOSES lends itself to the experimentation of alternative approaches to QoS-driven adaptation of service-oriented systems thanks to its modular architecture.